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Next Gen Commerce Cloud
23Sep

Next Gen Commerce Cloud

Salesforce has launched the next generation of Commerce Cloud, delivering a unified platform that connects B2C, DTC, and B2B commerce, along with Order Management, Payments, and more, to drive seamless customer experiences and revenue growth. With these innovations, businesses can scale across digital and physical channels while leveraging trusted AI and enterprise-wide data for smarter operations. Next Gen Commerce Cloud. Key features include Autonomous Agentforce Agents, which enhance commerce for merchants, buyers, and shoppers by automating tasks such as product recommendations and order tracking. Companies like MillerKnoll have seen success by using Commerce Cloud’s innovations to scale their workforce and drive revenue across multiple channels. New Agentforce Agents for Commerce — Merchant, Buyer, and Personal Shopper — autonomously manage tasks and improve the customer journey. They handle tasks without human intervention, such as product recommendations or order lookups, drawing insights from rich data sources like customer interactions, inventory, orders, and reviews. By tapping into unified data, these agents augment employees, offering tailored experiences and increasing efficiency, while strictly adhering to privacy and security standards. Salesforce’s Commerce Cloud now natively integrates every part of the commerce journey, helping businesses break down data silos and offer consistent, personalized interactions. As Michael Affronti, SVP and GM of Commerce Cloud, highlights: “Unified commerce is the future, breaking down silos to deliver seamless experiences across all channels.” Key new features and functionalities include: With these advancements, Commerce Cloud empowers businesses to create seamless, AI-powered experiences that drive customer loyalty, operational efficiency, and revenue growth across every touchpoint. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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September 23, 2024in Data, Enterprise, Google, Salesforce, Salesforce Commerce Cloud
Is Agentforce Different?
22Sep

Is Agentforce Different?

The Salesforce hype machine is in full swing, with product announcements like Chatter, Einstein GPT, and Data Cloud, all positioned as revolutionary tools that promise to transform how we work. Is Agentforce Different? However, it’s often difficult to separate fact from fiction in the world of Salesforce. The cloud giant thrives on staying ahead of technological advancements, which means reinventing itself every year with new releases and updates. You could even say three times per year with the major releases. Why Enterprises Need Multiple Salesforce Orgs Over the past decade, Salesforce product launches have been hit or miss—primarily miss. Offerings like IoT Cloud, Work.com, and NFT Cloud have faded into obscurity. This contrasts sharply with Salesforce’s earlier successes, such as Service Cloud, the AppExchange, Force.com, Salesforce Lightning, and Chatter, which defined its first decade in business. One notable exception is Data Cloud. This product has seen significant success and now serves as the cornerstone of Salesforce’s future AI and data strategy. With Salesforce’s growth slowing quarter over quarter, the company must find new avenues to generate substantial revenue. Artificial Intelligence seems to be their best shot at reclaiming a leadership position in the next technological wave. Is Agentforce Different? While Salesforce has been an AI leader for over a decade, the hype surrounding last year’s Dreamforce announcements didn’t deliver the growth the company was hoping for. The Einstein Copilot Studio—comprising Copilot, Prompt Builder, and Model Builder—hasn’t fully lived up to expectations. This can be attributed to a lack of AI readiness among enterprises, the relatively basic capabilities of large language models (LLMs), and the absence of fully developed use cases. In Salesforce’s keynote, it was revealed that over 82 billion flows are launched weekly, compared to just 122,000 prompts executed. While Flow has been around for years, this stat highlights that the use of AI-powered prompts is still far from mainstream—less than one prompt per Salesforce customer per week, on average. When ChatGPT launched at the end of 2022, many predicted the dawn of a new AI era, expecting a swift and dramatic transformation of the workplace. Two years later, it’s clear that AI’s impact has yet to fully materialize, especially when it comes to influencing global productivity and GDP. However, Salesforce’s latest release feels different. While AI Agents may seem new to many, this concept has been discussed in AI circles for decades. Marc Benioff’s recent statements during Dreamforce reflect a shift in strategy, including a direct critique of Microsoft’s Copilot product, signaling the intensifying AI competition. This year’s marketing strategy around Agentforce feels like it could be the transformative shift we’ve been waiting for. While tools like Salesforce Copilot will continue to evolve, agents capable of handling service cases, answering customer questions, and booking sales meetings instantly promise immediate ROI for organizations. Is the Future of Salesforce in the Hands of Agents? Despite the excitement, many questions remain. Are Salesforce customers ready for agents? Can organizations implement this technology effectively? Is Agentforce a real breakthrough or just another overhyped concept? Agentforce may not be vaporware. Reports suggest that its development was influenced by Salesforce’s acquisition of Airkit.AI, a platform that claims to resolve 90% of customer queries. Salesforce has even set up dedicated launchpads at Dreamforce to help customers start building their own agents. Yet concerns remain, especially regarding Salesforce’s complexity, technical debt, and platform sprawl. These issues, highlighted in this year’s Salesforce developer report, cannot be overlooked. Still, it’s hard to ignore Salesforce’s strategic genius. The platform has matured to the point where it offers nearly every functionality an organization could need, though at times the components feel a bit disconnected. For instance: Salesforce is even hinting at usage-based pricing, with a potential $2 charge per conversation—an innovation that could reshape their pricing model. Will Agents Be Salesforce’s Key to Future Growth? With so many unknowns, only time will tell if agents will be the breakthrough Salesforce needs to regain the momentum of its first two decades. Regardless, agents appear to be central to the future of AI. Leading organizations like Copado are also launching their own agents, signaling that this trend will define the next phase of AI innovation. In today’s macroeconomic environment, where companies are overstretched and workforce demands are high, AI’s ability to streamline operations and improve customer service has never been more critical. Whoever cracks customer service AI first could lead the charge in the inevitable AI spending boom. We’re all waiting to see if Salesforce has truly cracked the AI code. But one thing is certain: the race to dominate AI in customer service has begun. And Salsesforce may be at the forefront. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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September 22, 2024in Agentforce Platform, Artificial Intelligence, Data, Enterprise, Google, Salesforce, Snowflake, Technology
Agentforce and Thinking AI
21Sep

Agentforce and Thinking AI

Agentforce is how humans with AI drive customer success together, equips organizations with autonomous agents that boost scale, efficiency, and satisfaction across service, sales, marketing, commerce, and more New Agentforce Atlas Reasoning Engine autonomously analyzes data, makes decisions, and completes tasks, providing reliable and accurate results With Agentforce, any organization can build, customize, and deploy their own agents quickly and easily, with low-code tools New Agentforce Partner Network allows customers to deploy pre-built agents and use agent actions from partners like Amazon Web Services, Google, IBM, Workday, and more Customers like OpenTable, Saks, and Wiley are turning to Agentforce because it is integrated with their apps, works across customer channels, augments their employees, and scales capacity for business needs SAN FRANCISCO — September 12, 2024 – Salesforce (NYSE: CRM), the world’s #1 AI CRM, today unveiled Agentforce, a groundbreaking suite of autonomous AI agents that augment employees and handle tasks in service, sales, marketing, and commerce, driving unprecedented efficiency and customer satisfaction. Agentforce enables companies to scale their workforces on demand with a few clicks. Agentforce’s limitless digital workforce of AI agents can analyze data, make decisions, and take action on tasks like answering customer service inquiries, qualifying sales leads, and optimizing marketing campaigns. With Agentforce, any organization can easily build, customize, and deploy their own agents for any use case across any industry. The future of AI is agents, and it’s here. Our vision is bold: to empower one billion agents with Agentforce by the end of 2025. This is what AI is meant to be.” MARC BENIOFF, CHAIR, CEO & CO-FOUNDER, SALESFORCE “Agentforce represents the Third Wave of AI—advancing beyond copilots to a new era of highly accurate, low-hallucination intelligent agents that actively drive customer success. Unlike other platforms, Agentforce is a revolutionary and trusted solution that seamlessly integrates AI across every workflow, embedding itself deeply into the heart of the customer journey. This means anticipating needs, strengthening relationships, driving growth, and taking proactive action at every touchpoint,” said Marc Benioff, Chair and CEO, Salesforce. “While others require you to DIY your AI, Agentforce offers a fully tailored, enterprise-ready platform designed for immediate impact and scalability. With advanced security features, compliance with industry standards, and unmatched flexibility. Our vision is bold: to empower one billion agents with Agentforce by the end of 2025. This is what AI is meant to be.” In contrast to now-outdated copilots and chatbots that rely on human requests and struggle with complex or multi-step tasks, Agentforce offers a new level of sophistication by operating autonomously, retrieving the right data on demand, building action plans for any task, and executing these plans without requiring human intervention. Like a self-driving car, Agentforce uses real-time data to adapt to changing conditions and operates independently within an organizations’ customized guardrails, ensuring every customer interaction is informed, relevant, and valuable. And when desired, Agentforce seamlessly hands off to human employees with a summary of the interaction, an overview of the customer’s details, and recommendations for what to do next. Industry leaders like OpenTable, Saks, and Wiley are already experiencing the transformative power of Agentforce. For example, Agentforce is helping organizations like Wiley provide customers with dynamic, conversational self-service. Agentforce is configured to answer questions using Wiley’s knowledge base already built into Salesforce so it can automatically resolve account access. It also triages registration and payment issues, directing customers to the appropriate resources. With Agentforce handling routine inquiries, Wiley has seen an over 40% increase in case resolution, outperforming their old chatbot and giving their human agents more time to focus on complex cases. Why it Matters An estimated 41% of employee time is spent on repetitive, low-impact work, and 65% of desk workers believe generative AI will allow them to be more strategic, according to the Salesforce Trends in AI Report. Every company has more jobs to be done than the resources available to do them. As a result, many jobs go unaddressed or uncompleted. Agentforce provides relief to overstretched teams with its ability to scale capacity on demand so humans can focus on higher-touch, higher-value, and more strategic outcomes. The future of work is a hybrid workforce composed of humans with agents, enabling companies to compete in an ever-changing world. Supporting Customer Quotes “Piloting Agentforce has made a noticeable difference during one of our busiest periods — back-to-school season. It’s been exciting to go live with our first agent thanks to the no-code builder, and we’ve seen a more than 40% increase in case resolution, outperforming our old bot. Agentforce helps to manage routine responsibilities and free up our service teams for more complex cases.” – Kevin Quigley, Senior Manager, Continuous Improvement, Wiley “Every interaction that restaurants and diners have with our support team must be accurate, fast, and reflective of the hospitality that restaurants show their guests. Agentforce has incredible potential to help us deliver that high touch attentiveness and support while significantly freeing up our team to address more complex needs.” – George Pokorny, SVP Customer Success, OpenTable “As we advance our personalization strategy, we believe Agentforce and its AI-powered capabilities have the potential to make a real impact on our approach to customer engagement, raising the bar in luxury retail. Agentforce will improve our effectiveness across customer touchpoints, empowering our employees and augmenting their ability to deliver the elevated and more individualized shopping experiences for which Saks is known.” – Mike Hite, Chief Technology Officer, Saks Global Like1 Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced

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September 21, 2024in Data, Enterprise, Generative AI, Google, Salesforce, Technology
Collaborative Business Intelligence
20Sep

Collaborative Business Intelligence

Collaborative Business Intelligence: Connecting Data and Teams In today’s data-driven world, the ability to interact with business intelligence (BI) tools is essential for making informed decisions. Collaborative business intelligence (BI), also known as social BI, allows users to engage with their organization’s data and communicate with data experts through the same platforms where they already collaborate. While self-service BI empowers users to generate insights, understanding the data’s context is critical to avoid misunderstandings that can derail decision-making. Collaborative BI integrates BI tools with collaboration platforms to bridge the gap between data analysis and communication, reducing the risks of misinterpretation. Traditional Business Intelligence Traditional BI involves the use of technology to analyze data and present insights clearly. Before BI platforms became widespread, data scientists and statisticians handled data analysis, making it challenging for non-technical professionals to digest the insights. BI evolved to automate visualizations, such as charts and dashboards, making data more accessible to business users. Previously, BI reports were typically available only to high-level executives. However, modern self-service BI tools democratize access, enabling more users—regardless of technical expertise—to create reports and visualize data, fostering better decision-making across the organization. The Emergence of Collaborative BI Collaborative BI is a growing trend, combining BI applications with collaboration tools. This approach allows users to work together synchronously or asynchronously within a shared platform, making it easier to discuss data reports in real time or leave comments for others to review. Whether it’s through Slack, Microsoft Teams, or social media apps, users can receive and discuss BI insights within their usual communication channels. This seamless integration of BI and collaboration tools offers a competitive edge, simplifying the process of sharing knowledge and clarifying data without switching between applications. Key Benefits of Collaborative Business Intelligence Leading Collaborative BI Platforms Here’s a look at some of the top collaborative BI platforms driving innovation in the market: Conclusion Collaborative BI empowers organizations by improving decision-making, democratizing data access, optimizing data quality, and ensuring data security. By integrating BI tools with collaboration platforms, businesses can streamline their operations, foster a culture of data-driven decision-making, and enhance overall efficiency. Choosing the right platform is key to maximizing the benefits of collaborative BI. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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September 20, 2024in Data, Google, Salesforce, Technology
Apple New AI
19Sep

Apple New AI

Apple Unveils New AI Features at “Glowtime” Event In typical fashion, Apple revealed its latest product updates on Monday with a pre-recorded keynote titled “Glowtime,” referencing the glowing ring around the screen when Apple Intelligence is activated. Though primarily a hardware event, the real highlight was the suite of AI-powered features coming to the new iPhone models this fall. The 98-minute presentation covered updates to iPhones, AirPods, and the Apple Watch, with Apple Intelligence being the thread tying together user experiences across all devices. MacRumors has published a detailed list of all announcements, including the sleep apnea detection feature for the Apple Watch and new hearing health tools for AirPods Pro 2. Key AI Developments for Brand Marketers Apple Intelligence was first introduced at its WWDC event in June, focusing on using Apple’s large language model (LLM) to perform tasks on-device with personalized results. It draws from user data in native apps like Calendar and Mail, enabling AI to handle tasks like image generation, photo searches, and AI-generated notifications. The keynote also introduced a new “Visual Intelligence” feature for iPhone 16 models, acting as a native visual search tool. By pressing the new “camera control” button, users can access this feature to perform searches directly from their camera, such as getting restaurant info or recognizing a dog breed. Apple’s AI-powered visual search offers a strategic opportunity for brands. The information for local businesses is pulled from Apple Maps, which relies on sources like Yelp and Foursquare. Brands should ensure their listings are well-maintained on these platforms and consider optimizing their digital presence for visual search tools like Google Lens, which integrates with Apple’s search. The Camera as an Input Device and the Rise of Spatial Content The camera’s role as an input device has been expanding, with Apple emphasizing photography as a key feature of its new iPhones. This year, the iPhone 16 introduces a new camera control button, offering enhanced haptic feedback for smoother control. Third-party apps like Snapchat will also benefit from this addition, giving users more refined camera capabilities. More importantly, iPhone 16 models can now capture spatial content, including both photos and audio, optimized for the Vision Pro mixed-reality headset. Apple’s move to integrate spatial content aligns with its goal to position the iPhone as a professional creator tool. Brands can capitalize on this by exploring augmented reality (AR) features or creating immersive user-generated content experiences. Apple’s Measured Approach to AI While Apple is clearly pushing AI, it is taking a cautious, phased approach. Though the new iPhones will hit the market soon, the full range of Apple Intelligence features will roll out gradually, starting in October with tools like the AI writing assistant and photo cleanup. More advanced features will debut next spring. This measured approach allows Apple to fine-tune its AI, avoiding rushed releases that could compromise user experience. For brands, this offers a lesson in pacing AI adoption: prioritize quality and customer experience over speed. Rather than rushing to integrate AI, companies should take time to understand how it can meaningfully enhance user interactions, focusing on trust and consistency to maintain customer loyalty. By following Apple’s lead and gradually introducing AI capabilities, brands can build trust, sustain anticipation, and ensure they offer technology that genuinely improves the customer experience. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more Top Ten Reasons Why Tectonic Loves the Cloud The Cloud is Good for Everyone – Why Tectonic loves the cloud You don’t need to worry about tracking licenses. Read more

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September 19, 2024in Data, Google, Technology
ChatGPT for Keywords
19Sep

ChatGPT for Keywords

Maximizing SEO on a Budget: A Guide for Business Owners For business owners working within tight budgets, stretching every marketing dollar is crucial. While hiring expensive SEO experts can be tempting, there’s a wealth of untapped keywords that are already working for your competitors. The key is to uncover them and use them to your advantage. No need for costly SEO tools—there are simple ways to spy on competitors’ keywords and create engaging content, all with free resources like ChatGPT. 1. Analyze Competitor Content Using ChatGPT That blog post from a competitor ranking above yours? It holds valuable keyword insights. By copying the link and asking ChatGPT to analyze it, you can easily discover the keywords they’re targeting. Simply ask: “ChatGPT, based on this content, what keywords is my competitor targeting?” ChatGPT will break down the keywords, providing insights you can use to optimize your own content. 2. Spy on Competitors’ Sitemaps A website’s sitemap is like a blueprint, showing how everything is organized. To access a competitor’s sitemap, simply add /sitemap.xml to the end of their URL. For example, if your competitor’s site is example.com, you would visit example.com/sitemap.xml. Once you access their sitemap, copy the URLs and ask ChatGPT to extract relevant keywords for you. This method is a goldmine for discovering what content your competitors are focusing on. 3. Use Search Operators for Targeted Research Search operators are powerful tools that let you search a competitor’s site with precision. For example, typing site:competitor.com SEO in Google will display all the SEO-related content from that competitor. To make keyword extraction even easier, use a tool like the SERP Snippet Extractor from the Chrome Web Store. Once you’ve gathered the titles, paste them into ChatGPT to extract keywords. 4. Check Keyword Volume with Google Keyword Planner Once you’ve gathered a list of keywords, head over to Google Keyword Planner (create a free Google Ads account if you don’t already have one). Use the “Get Search Volume” option to see search volumes and competition levels for your keywords. Pay close attention to suggested related keywords, as they can offer additional opportunities. Checking trends for seasonal patterns can also help you time your content for maximum impact. Final Thoughts Leveraging free tools like ChatGPT can help business owners on a budget optimize their SEO strategies without breaking the bank. By analyzing competitor content, spying on sitemaps, and using search operators, you can uncover valuable keywords and improve your website’s ranking—all without costly investments. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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September 19, 2024in Google, Salesforce
Impact of EHR Adoption
14Sep

Impact of EHR Adoption

Fueled by the availability of chatbot interfaces like Chat-GPT, generative AI has become a key focus across various industries, including healthcare. Many electronic health record (EHR) vendors are integrating the technology to streamline administrative workflows, allowing clinicians to focus more on patient care. Whether you see EHR adoption as easy or challenging, the Impact of EHR Adoption will be positive. Generative AI and EHR Efficiency As defined by the Government Accountability Office (GAO), generative AI is “a technology that can create content, including text, images, audio, or video, when prompted by a user.” Generative AI systems learn patterns from vast datasets, enabling them to generate new, similar content using machine learning algorithms and statistical models. One of the areas where generative AI shows promise is in automating EHR workflows, which could alleviate the burden on clinicians. Epic’s AI-Driven Innovations Phil Lindemann, vice president of data and analytics at Epic, noted that generative AI is ideal for automating repetitive tasks. One application under testing allows the technology to draft patient portal message responses for clinicians to review and send. This could save time and let doctors spend more time with patients. Another project focuses on summarizing updates to a patient’s record since their last visit, offering a quick synopsis for the provider. Epic is also exploring how generative AI could help patients better understand their health records by translating complex medical terms into more accessible language. Additionally, the system can translate this information into various languages, enhancing patient education across diverse populations. However, Lindemann emphasized that while AI offers valuable tools, it is not a cure-all for healthcare’s challenges. “We see it as a translation tool,” he said, acknowledging the importance of targeted use cases for successful implementation. Oracle Health’s Clinical Digital Assistant Oracle Health is beta-testing a generative AI chatbot aimed at reducing administrative tasks for healthcare professionals. The Clinical Digital Assistant summarizes patient information and generates automated clinical notes by listening to patient-provider conversations. Physicians can interact with the tool during consultations, asking for relevant patient data without breaking eye contact with the patient. The assistant can also suggest actions based on the discussion, which providers must review before finalizing. Oracle plans to make this tool widely available by the second quarter of 2024, with the goal of easing clinician workloads and improving the patient experience. eClinicalWorks and Ambient Listening Technology In partnership with sunoh.ai, eClinicalWorks is utilizing generative AI-powered ambient listening technology to assist with clinical documentation. This tool automatically drafts clinical notes based on patient conversations, which clinicians can then review and edit as necessary. Girish Navani, CEO of eClinicalWorks, highlighted the potential for generative AI to become a personal assistant for doctors, streamlining documentation tasks and reducing cognitive load. The integration is expected to be available to customers in early 2024. MEDITECH’s AI-Powered Discharge Summaries MEDITECH is collaborating with Google to develop a generative AI tool focused on automating hospital discharge summaries. These summaries, which are crucial for care coordination, are often time-consuming for clinicians to create, especially for patients with longer hospital stays. The AI system generates draft summaries that clinicians can review and edit, aiming to speed up discharges and reduce clinician burnout. MEDITECH is working with healthcare organizations to validate the technology before a general release. Helen Waters, executive vice president and COO of MEDITECH, stressed the importance of careful implementation. The goal is to ensure accuracy and build trust among clinicians so that generative AI can be successfully integrated into clinical workflows. The Impact of EHR Adoption EHR systems have transformed healthcare, improving care coordination and decision support. However, EHR-related administrative burdens have also contributed to clinician burnout. A 2019 study found that 40% of physician burnout was linked to EHR use. By automating time-consuming EHR tasks, generative AI could help reduce this burden and improve clinical efficiency. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more Top Ten Reasons Why Tectonic Loves the Cloud The Cloud is Good for Everyone – Why Tectonic loves the cloud You don’t need to worry about tracking licenses. Read more

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September 14, 2024in Data, Generative AI, Google, Salesforce Health and Life Sciences Solutions, Salesforce Optimization, Technology
Salesforce and Qatalog
09Sep

Salesforce and Qatalog

Conversational AI for Salesforce Supercharge your Salesforce workflows with the power of AI. Whether you’re tracking deals, reviewing pipeline performance, or uncovering insights, Qatalog’s AI assistant simplifies it all with natural language queries. Designed to understand the intent behind your questions, it delivers accurate, context-rich answers—no manual reporting required. Whether you’re a Salesforce novice or a seasoned pro, Salesforce and Qatalog redefine how you engage with your CRM data. Key Features Salesforce and Qatalog Conversational Search Say goodbye to navigating complex dashboards and reports. Just ask straightforward questions like: Get instant, actionable answers powered by AI, saving time and effort. No Technical Expertise Needed Qatalog’s intuitive AI chat interface is designed for everyone. Non-technical users can quickly access insights without needing Salesforce expertise, freeing up technical teams to focus on higher-value tasks. Seamless Integrations Connect Salesforce with your favorite business tools, including Outlook, Google Drive, Slack, and more. Access Salesforce CRM data in context across your apps, streamlining workflows and collaboration. Enterprise-Grade Data Security Your data’s privacy is paramount. Qatalog processes Salesforce data securely in real-time and discards it immediately after use, ensuring sensitive information stays protected. Transform the way you work with Salesforce—ask, explore, and act with confidence using Qatalog’s Conversational AI. Salesforce and Qatalog. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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September 9, 2024in Data, Enterprise, Google, Salesforce
Converting 15-Character IDs to 18-Character in Salesforce
02Sep

Converting 15-Character IDs to 18-Character in Salesforce

In Salesforce, every record is assigned a unique Record ID, which is essential for managing data, writing formulas, and referencing records as an admin or developer. There are two types of Record IDs: a 15-character version and an 18-character version, each suited for different scenarios. Converting 15-character IDs to 18-character ones can be time-consuming when done manually, but several tools and methods can simplify the process, allowing for instant conversion with just a click. Understanding Salesforce Record IDs 15-Character Record ID The 15-character Record ID is case-sensitive and typically used in Salesforce’s user interface for tasks like editing records and generating reports. However, its case sensitivity can create issues with systems that do not recognize differences between uppercase and lowercase letters. 18-Character Record ID To mitigate case sensitivity issues, Salesforce offers an 18-character ID, which is used in APIs and tools such as Data Loader. This ID adds three additional characters to the 15-character version and is always returned by these tools during data exports. When to Use Each ID For consistency, the 18-character ID is preferable, especially when working with external systems. It’s best practice to use the 18-character ID in formulas, API calls, or any data comparisons to avoid errors caused by case sensitivity. Converting IDs Using a Formula Field in Salesforce Salesforce recommends creating a formula field with the CASESAFEID(Id) function to convert the 15-character ID to an 18-character ID. Here are some key points to consider: Implementation Steps: Once completed, this formula field will display the 18-character ID on relevant records. APIs and Software DevelopmentIf you need a more scalable or efficient solution, consider using Salesforce APIs or third-party tools for ID conversion. While online tools may suffice for small tasks, they can become unwieldy when handling hundreds or thousands of records in a CSV or Excel file. Streamlining ID Conversion with Xappex Tools Imagine the frustration of manually copying and pasting IDs! That’s where the XL-Connector and G-Connector from Xappex come into play. These tools work directly in Excel or Google Sheets, simplifying the ID conversion process. Instead of juggling multiple tools or navigating complex processes, you can seamlessly convert Salesforce IDs within your spreadsheet, saving significant time and effort. Using XL-Connector for ID Conversion in Excel Using G-Connector (Google Sheets) for ID Conversion G-Connector is Xappex’s integration tool for Google Sheets and Salesforce. If you haven’t installed it yet, do so and log in to your Salesforce org. The sheet will automatically update with the new 18-character IDs and provide links to open the records directly in Salesforce. Conclusion In summary, managing Salesforce Record IDs doesn’t have to be a hassle. While converting 15-character IDs to 18-character IDs is crucial for consistency, doing it manually can be tedious. With XL-Connector and G-Connector, you can streamline ID conversion with just a click in Excel or Google Sheets, making your workflow much more efficient. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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September 2, 2024in Data, Google, Salesforce
AI and Big Data
31Aug

AI and Big Data

Over the past decade, enterprises have accumulated vast amounts of data, capturing everything from business processes to inventory statistics. This surge in data marked the onset of the big data revolution. However, merely storing and managing big data is no longer sufficient to extract its full value. As organizations become adept at handling big data, forward-thinking companies are now leveraging advanced analytics and the latest AI and machine learning techniques to unlock even greater insights. These technologies can identify patterns and provide cognitive capabilities across vast datasets, enabling organizations to elevate their data analytics to new levels. Additionally, the adoption of generative AI systems is on the rise, offering more conversational approaches to data analysis and enhancement. This allows organizations to extract significant insights from information that would otherwise remain untapped in data stores. How Are AI and Big Data Related? Applying machine learning algorithms to big data is a logical progression for companies aiming to maximize the potential of their data. Unlike traditional rules-based approaches that follow explicit instructions, machine learning systems use data-driven algorithms and statistical models to analyze and detect patterns in data. Big data serves as the raw material for these systems, which derive valuable insights from it. Organizations are increasingly recognizing the benefits of integrating big data with machine learning. However, to fully harness the power of both, it’s crucial to understand their individual capabilities. Understanding Big Data Big data involves extracting and analyzing information from large quantities of data, but volume is just one aspect. Other critical “Vs” of big data that enterprises must manage include velocity, variety, veracity, validity, visualization, and value. Understanding Machine Learning Machine learning, the backbone of modern AI, adds significant value to big data applications by deriving deeper insights. These systems learn and adapt over time without the need for explicit programming, using statistical models to analyze and infer patterns from data. Historically, companies relied on complex, rules-based systems for reporting, which often proved inflexible and unable to cope with constant changes. Today, machine learning and deep learning enable systems to learn from big data, enhancing decision-making, business intelligence, and predictive analysis. The strength of machine learning lies in its ability to discover patterns in data. The more data available, the more these algorithms can identify patterns and apply them to future data. Applications range from recommendation systems and anomaly detection to image recognition and natural language processing (NLP). Categories of Machine Learning Algorithms Machine learning algorithms generally fall into three categories: The most powerful large language models (LLMs), which underpin today’s widely used generative AI systems, utilize a combination of these methods, learning from massive datasets. Understanding Generative AI Generative AI models are among the most powerful and popular AI applications, creating new data based on patterns learned from extensive training datasets. These models, which interact with users through conversational interfaces, are trained on vast amounts of internet data, including conversations, interviews, and social media posts. With pre-trained LLMs, users can generate new text, images, audio, and other outputs using natural language prompts, without the need for coding or specialized models. How Does AI Benefit Big Data? AI, combined with big data, is transforming businesses across various sectors. Key benefits include: Big Data and Machine Learning: A Synergistic Relationship Big data and machine learning are not competing concepts; when combined, they deliver remarkable results. Emerging big data techniques offer powerful ways to manage and analyze data, while machine learning models extract valuable insights from it. Successfully handling the various “Vs” of big data enhances the accuracy and power of machine learning models, leading to better business outcomes. The volume of data is expected to grow exponentially, with predictions of over 660 zettabytes of data worldwide by 2030. As data continues to amass, machine learning will become increasingly reliant on big data, and companies that fail to leverage this combination will struggle to keep up. Examples of AI and Big Data in Action Many organizations are already harnessing the power of machine learning-enhanced big data analytics: Conclusion The integration of AI and big data is crucial for organizations seeking to drive digital transformation and gain a competitive edge. As companies continue to combine these technologies, they will unlock new opportunities for personalization, efficiency, and innovation, ensuring they remain at the forefront of their industries. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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August 31, 2024in Data, Enterprise, Generative AI, Google, Salesforce, Technology
AI Services and Models Security Shortcomings
25Aug

AI Services and Models Security Shortcomings

Orca Report: AI Services and Models Show Security Shortcomings Recent research by Orca Security reveals significant security vulnerabilities in AI services and models deployed in the cloud. The “2024 State of AI Security Report,” released in 2024, underscores the urgent need for improved security practices as AI technologies advance rapidly. AI Services and Models Security Shortcomings. AI usage is exploding. Gartner predicts that the AI software market will grow19.1% annually, reaching 8 billion by 2027. In many ways, AI is now inthe stage reminiscent of where cloud computing was over a decade ago. Orca’s analysis of cloud assets across major platforms—AWS, Azure, Google Cloud, Oracle Cloud, and Alibaba Cloud—has highlighted troubling risks associated with AI tools and models. Despite the surge in AI adoption, many organizations are neglecting fundamental security measures, potentially exposing themselves to significant threats. The report indicates that while 56% of organizations use their own AI models for various purposes, a substantial portion of these deployments contain at least one known vulnerability. Orca’s findings suggest that although most vulnerabilities are currently classified as low to medium risk, they still pose a serious threat. Notably, 62% of organizations have implemented AI packages with vulnerabilities, which have an average CVSS score of 6.9. Only 0.2% of these vulnerabilities have known public exploits, compared to the industry average of 2.5%. Insecure Configurations and Controls Orca’s research reveals concerning security practices among widely used AI services. For instance, Azure OpenAI, a popular choice for building custom applications, was found to be improperly configured in 27% of cases. This lapse could allow attackers to access or manipulate data transmitted between cloud resources and AI services. The report also criticizes default settings in Amazon SageMaker, a prominent machine learning service. It highlights that 45% of SageMaker buckets use non-randomized default names, and 98% of organizations have not disabled default root access for SageMaker notebook instances. These defaults create vulnerabilities that attackers could exploit to gain unauthorized access and perform actions on the assets. Additionally, the report points out a lack of self-managed encryption keys and encryption protection. For instance, 98% of organizations using Google Vertex have not enabled encryption at rest for their self-managed keys, potentially exposing sensitive data to unauthorized access or alteration. Exposed Access Keys and Platform Risks Security issues extend to popular AI platforms like OpenAI and Hugging Face. Orca’s report found that 20% of organizations using OpenAI and 35% using Hugging Face have exposed access keys, heightening the risk of unauthorized access. This follows recent research by Wiz, which demonstrated vulnerabilities in Hugging Face during Black Hat USA 2024, where sensitive data was compromised. Addressing the Security Challenge Orca co-founder and CEO Gil Geron emphasizes the need for clear roles and responsibilities in managing AI security. He stresses that security practitioners must recognize and address these risks by setting policies and boundaries. According to Geron, while the challenges are not new, the rapid development of AI tools makes it crucial to address security from both engineering and practitioner perspectives. Geron also highlights the importance of reviewing and adjusting default settings to enhance security, advocating for rigorous permission management and network hygiene. As AI technology continues to evolve, organizations must remain vigilant and proactive in safeguarding their systems and data. In conclusion, the Orca report serves as a critical reminder of the security risks associated with AI services and models. Organizations must take concerted action to secure their AI deployments and protect against potential vulnerabilities. Balance Innovation and Security in AI Tectonic notes Salesforce was not included in the sampling. Content updated September 2024. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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August 25, 2024in AI Tools, Data, Google, Technology
Understanding AI Agents
06Aug

Understanding AI Agents

Understanding AI Agents: A Comprehensive Guide Artificial Intelligence (AI) has come a long way, offering systems that automate tasks and provide intelligent, responsive solutions. One key concept within AI is the AI agent—an autonomous system capable of perceiving its environment and taking actions to achieve specific goals. This guide explores AI agents, their types, working mechanisms, and how to build them using platforms like Microsoft Autogen and Google Vertex AI Agent Builder. It also highlights how companies like LeewayHertz and Markovate can assist in the development of AI agents. What is an AI Agent? AI agents are systems designed to interact with their environment autonomously. They process inputs, make decisions, and execute actions based on predefined rules or learned experiences. These agents range from simple rule-based systems to complex machine learning models that adapt over time. Types of AI Agents AI agents can be classified based on complexity and functionality: How AI Agents Work The working mechanism of an AI agent involves four key components: Architectural Blocks of an Autonomous AI Agent An autonomous AI agent typically includes: Building an AI Agent: The Basics Building an AI agent involves several essential steps: Microsoft Autogen: A Platform Overview Microsoft Autogen is a powerful tool for building AI agents, offering a range of features that simplify the development, training, and deployment process. Its user-friendly interface allows developers to create custom agents quickly. Key Steps to Building AI Agents with Autogen: Benefits of Autogen: Vertex AI Agent Builder: Enabling No-Code AI Development Google’s Vertex AI Agent Builder simplifies AI agent development through a no-code platform, making it accessible to users without extensive programming experience. Its drag-and-drop functionality allows for quick and efficient AI agent creation. Key Features of Vertex AI Agent Builder: Conclusion AI agents play a critical role in automating decision-making and performing tasks independently. Platforms like Microsoft Autogen and Google Vertex AI Agent Builder make the development of these agents more accessible, providing powerful tools for both novice and experienced developers. By leveraging these technologies and partnering with companies like LeewayHertz and Markovate, businesses can build custom AI agents that enhance automation, decision-making, and operational efficiency. Whether you’re starting from scratch or looking to integrate AI capabilities into your existing systems, the right tools can make the process seamless and effective. How do you think these tools stack up next to Salesforce AI Agents? Comment below. Content updated October 2024. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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August 6, 2024in AI Tools, Artificial Intelligence, Data, Google
Alphabet Abandons Acquisition for HubSpot
10Jul

Alphabet Abandons Acquisition for HubSpot

Alphabet Abandons Acquisition Plans for HubSpot The integration between Salesforce and Hubspot could have changed drastically. The HubSpot-Salesforce integration allows you to pass data between HubSpot and Salesforce seamlessly, and maintain consistency between your marketing and sales teams. Current HubSpot Google integration includes: ability to log emails sent from Gmail into HubSpot CRM with one click, so your team spends less time on busy work and more time doing what they do best. HubSpot integrates with your Google Calendar to help you book more meetings in less time. Google parent Alphabet has abandoned its plans to acquire HubSpot, according to sources familiar with the matter. This decision puts to rest what would have been one of the year’s largest takeovers. HubSpot, Inc. is an American developer and marketer of software products for inbound marketing, sales, and customer service. HubSpot was founded by Brian Halligan and Dharmesh Shah in 2006. The talks between Alphabet and HubSpot never progressed to due diligence and fell apart shortly after the companies held initial discussions on a potential deal, the source said, on condition of anonymity to discuss confidential matters. HubSpot’s shares, a customer relationship management company, plummeted by as much as 19 percent on Wednesday (Jul 10) in New York trading, marking the most significant drop since 2020. The shares closed down 12 percent at $492.31, giving the company a market value of approximately $25 billion. Earlier this year, Alphabet had expressed interest in a potential deal with HubSpot. However, the two sides never progressed to detailed discussions or due diligence, said the sources, who requested anonymity due to the confidentiality of the matter. Representatives for Alphabet did not immediately comment. A HubSpot spokesperson also declined to comment. Any acquisition of HubSpot would have been among the largest tech deals of the year, comparable to Synopsys’s pending $34 billion acquisition of Ansys, according to data compiled by Bloomberg. HubSpot recently suffered a hack attack. HubSpot, which builds marketing software for small and medium-sized businesses, has specialized in so-called inbound marketing, where consumers start engagement with a brand. HubSpot customers apply its software to make advertising content that consumers can click on. CEO Yamini Rangan said in May on HubSpot’s financial results call that customer demand had weakened, as small businesses worried about the economic impact of high interest rates. Acquiring Cambridge, Massachusetts-based HubSpot, which caters to small and midsize enterprises, would have bolstered Alphabet’s competitiveness against rivals like Microsoft, Oracle, and Salesforce. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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July 10, 2024in Data, Enterprise, Google, Salesforce

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